Error Analysis of Taiwanese University Students’ English Essay Writing: A Longitudinal Corpus Study

Abstract

Writing is considered one of the most difficult skills in EFL/ESL. Thus, meticulous recognition and classification of students' errors in certain contexts is a worthwhile endeavor which provides us with both diagnostic and prognostic power. Accordingly, a total of 430 students in 15 English writing classes held during 12 consecutive semesters in a private university in central Taiwan were the subjects of this study. They composed 5703 essays which were rated and coded by the authors. Adopting and modifying the error taxonomy proposed by Zheng and Park (2013), the authors classified a sum of 63460 errors into four main groups with their subsequent subcategories. This study revealed that the highest problematic areas for Taiwanese university students were 'misformation' with 51.55% of the whole including errors in tenses, parts of speech, prepositions, subject/verb agreements, and run-on sentences. Then, 'omission' errors ranked second with 21.30% including errors in articles, plural suffix-s, and relative pronouns. Finally, the third and fourth error types were 'others' with 15.13% including spelling, capitalization, and wrong vocabulary, and 'addition' with 12.01% containing errors in articles, unnecessary words, and conjunctions. This study provides numerous genuine samples from the students' compositions being annotated based on the applied error taxonomy. Thus, the data presented in this study can provide researchers with a practical framework for future studies in error analysis, as well as pedagogical implications in the field.

Synthesizing the Attributes of Computer-Based Error Analysis for ESL and EFL Learning: A Scoping Review

“…• Autocorrection: Certain errors are automatically corrected by the software without the author's knowledge, resulting in erroneous analyses. While explaining reasons for not employing software for EA, Shirban Sasi [67] mentioned that the software may automatically rectify various problems, such as spelling, punctuation, and even word choice, without the researcher's knowledge. A study by Barrot [32] employing Grammarly required learners to turn off the autocorrect feature as protocol to prevent the software from prescreening the text.…”

“…Misleading Feedback: CBEA as employed in grammar checkers often provides corrective feedback to correct erroneous words or sentences. However, researchers employing Grammarly, CYWrite, and Write&Improve found that, on certain occasions, the feedback given could divert the meaning of the sentence; this situation occurred when the suggested answers were not suitable with respect to the intentions of the sentence [33,45,67]. The feedback provided by Grammarly is not in line with the intentions of the users [27,42,68].…”